If you read my last update, you’ll have seen me talk about AI agents and how they represent the vehicles of change for the insurance industry. AI agents are essentially AI-powered systems that are trained to perform particular actions autonomously, for example, renewal comparisons, or retrieving risk data.
You could think of them as players in an orchestra. Individually, each has a single instrument and on their own can produce a decent tune. But, bring a number of these players together, working in harmony and you create a symphony.
The more technical-minded among you may think of AI agents as assembly line workers. Individually, these workers play an important role in the production process, but it’s through organising these workers into a structured process that they can achieve a great end product.
Agents of underwriting
Many stages of the underwriting process are perfect for the deployment of AI agents, and individually, any one of these could save an underwriter a lot of time and manual effort. However, if we could combine a number of these agents, and allow them to collaborate on these tasks? Well, then we can revolutionise insurance underwriting.
The concept of an “agentic workflow” is relatively new. Though we’ve been talking about automating parts of the insurance underwriting process for a long time, until recently, these automated elements were largely siloed. Individually, these automations helped underwriters to work more efficiently and removed a lot of the tedious tasks underwriters hate, but joining these point processes via an agentic workflow has the power to increase efficiencies even more and help underwriters to focus their attention on the art of their job.
Let’s look at an example of an agentic workflow for insurance underwriting.
Review agent: An AI agent can be initially deployed to extract and validate information from a submission, ensuring all required documentation and information is present. The underwriter then knows they’re looking at a valid submission and have everything they need to produce a quote.
Data validation agent: Humans are good at spotting patterns in data, but AI is even better. A data validation agent can comb through millions of data points and alert underwriters to new trends that humans may miss, these agents can present a full picture to the underwriter and help them to better contextualise the risk.
Risk assessment agent: Another agent can compare the extracted risk data with the insurers’ risk appetite and autonomously decide on whether the risk falls in or out of appetite. Underwriters can then focus their attention only on the best, most profitable risks, rather than wasting valuable time on those outside of appetite.
Compliance agent: This agent can automatically run sanctions checks to ensure the risk meets the insurers’ legal and regulatory guidelines. Again, underwriters then know they are dealing with a “safe” risk, rather than spending a lot of time researching the risk, only to discover it raises a number of critical red flags.
Binding agent: No, not the cookery ingredient. This agent can “read” the information generated from its agent counterparts and present an underwriter with a decision on whether or not to bind the presented risk.
Aside from the clear operational efficiencies, there are numerous benefits of an agentic workflow.
The ability to quickly retrieve and assess vast amounts of data can enhance accuracy and, facilitate better risk management, and lead to more consistent and objective evaluation of risks. These workflows enable real-time decision-making and adaptability, allowing for swift responses to evolving conditions and regulatory changes. Additionally, their scalability leads to long-term cost savings for insurance companies, while ensuring transparency and compliance through detailed audit trails.
Conducting the orchestra
Integrating any one of these agents into an insurance system isn’t too difficult, unless you’re working within a landlocked legacy system, of course… the key is piecing them all together under one orchestration layer to ensure they’re working together seamlessly, and underwriters can view their outputs in one place, at the right stage of the underwriting journey. That’s where the Send Underwriting Workbench comes in.
This year, we’re doubling down on AI enablement, working with our customers and strategic integration partners to build and integrate the right agents, join the dots and create beautiful agentic workflows that underwriters enjoy using.
Our aim is to help our customers take advantage of the ecosystem of integrations, data, and AI tools they need to fuel the next stage of their growth. Can we help you?
We’d love to explore what an agentic workflow could look like for your business. Contact the team to learn more!
Matt McGrillis, co-founder and Chief Product Officer, Send